AI Engineering Team Lead - Sovereign AI Engineering

At Dream, we redefine cyber defense vision by combining AI and human expertise to create products that protect nations and critical infrastructure. This is more than a job; it’s a Dream job. Dream is where we tackle real-world challenges, redefine AI and security, and make the digital world safer. Let’s build something extraordinary together.

Dream's AI cybersecurity platform applies a new, out-of-the-ordinary, multi-layered approach, covering endless and evolving security challenges across the entire infrastructure of the most critical and sensitive networks. Built as part of a broader sovereign AI platform, our technology is designed to operate in on-premise, private cloud, and air-gapped environments, enabling nations to maintain full control over their data, infrastructure, and AI capabilities. Central to Dream's proprietary Cyber Language Models are innovative technologies that provide contextual intelligence for the future of cybersecurity.

At Dream, our talented team, driven by passion, expertise, and innovative minds, inspires us daily. We are not just dreamers, we are dream-makers.

The Dream Job

It starts with you - a technical leader driven to build both the agentic AI platform and the engineering team behind it. You care about backend quality, platform reliability, and growing engineers through real ownership. Dream is AI-first across the board - every team builds and operates agents. You'll set the technical direction for the platform that makes this possible: agent orchestration frameworks, LLM gateways, evaluation infrastructure, tool-calling systems, and retrieval pipelines. Without this platform, agents don't ship - you own the layer that turns AI research into Sovereign AI products, deployed across cloud and on-prem environments. You stay close enough to the codebase to debug production incidents, unblock your engineers, and make sound architecture calls.

If you want to make a meaningful impact, join Dream's mission and lead the team that builds the agentic AI platform driving Sovereign AI products - this role is for you.

The Dream-Maker Responsibilities

• Architect and evolve the AI platform - agent orchestration, LLM gateways, context engineering pipelines, evaluation infrastructure, tool-calling systems, and retrieval pipelines - through RFCs, prototypes, and design reviews.
• Lead and grow a small team of AI Engineers building the agent framework, production backend services, and AI platform infrastructure - hire, mentor, pair on hard problems, and raise the bar through hands-on code and design reviews.
• Contribute to critical systems, debug production incidents, and maintain enough codebase context to make sound technical calls.
• Own reliability across AI and agent services - set and enforce SLAs, build observability for non-deterministic systems, and harden tool execution environments for cost and security.
• Set the standard for AI engineering practices - agent testing strategies, evaluation frameworks with human-in-the-loop oversight, retrieval quality benchmarks, and CI/CD for AI systems.
• Work closely with ML Platform, Data Platform, DevOps, Data Science, and Product teams across the Applied AI Engineering group - ensure the AI platform evolves to serve teams building agentic workflows across the organization.
• Measure and improve developer experience - deploy friction, onboarding time, CI turnaround - as seriously as system performance.

The Dream Skill Set

• 6+ years in backend software engineering, with 4+ years focused on production systems that integrate AI/ML models or LLMs.
• 2+ years leading an engineering team - hiring, mentoring, conducting design reviews, and shipping alongside your team.
• Engineering craft - Strong Python, Go, or Java, system architecture, API design, testing, and secure coding practices.
• Agentic systems & LLM integration - Deep understanding of agent orchestration, tool-use architectures, LLM integration patterns, context engineering, and frameworks like LangGraph or similar, or custom-built equivalents
• Backend & platform engineering — Experience building and operating production APIs, services, and platform infrastructure at scale; comfortable working with relational databases, message queues, and event-driven architectures
• RAG & retrieval - Experience with production RAG pipelines, vector databases, embedding systems, and retrieval quality
• Evaluation & observability - Experience building LLM and agent eval infrastructure, monitoring AI quality, and observability for non-deterministic systems

Nice to Have:

• Platform & infra - Kubernetes, AWS, Terraform or similar IaC, CI/CD, service architecture, incident management
• Experience with MCP or similar tool-use protocols for agent-to-service communication
• Hands-on ML experience - model training, fine-tuning, or working directly with ML pipelines

Never Stop Dreaming...

If you think this role doesn't fully match your skills but are eager to grow and break glass ceilings, we’d love to hear from you! 

Requirements